CN101527590A - Self-adaptive beam forming method and self-adaptive beam forming device - Google Patents
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Abstract
The invention discloses a method for a self-adaptive beam forming weight, which comprises the following steps that: after multipath sampling signals are received, the spatial covariance matrix estimation and the signal-to-noise ratio of the multipath sampling signals are acquired according to the multipath sampling signals; the amount of diagonal loading is acquired according to the signal-to-noise ratio, and the diagonal loading is performed on the spatial covariance matrix estimation according to the amount of diagonal loading; a training sequence is modulated to acquire an expected signal, and the multipath sampling signals and the expected signal are subjected to correlation operation to acquire a correlation vector; and the self-adaptive beam forming weight is generated according to the spatial covariance matrix estimation after the diagonal loading and the correlation vector, and the multipath sampling signals are subjected to weighted sum to output a self-adaptive beam signal according to the self-adaptive beam forming weight. The invention also correspondingly provides a self-adaptive beam forming device. Thus the method and the device can reduce the calculation amount during the formation of self-adaptive beams, improve the robustness of beam formation, and have simple realization.
Description
Technical field
The present invention relates to field of mobile communication, relate in particular to a kind of adaptive beam formation method and device.
Background technology
In recent years, along with increasing rapidly of wireless communication user number, the anti-interference problem of communication system such as GSM (GlobalSystem for Mobile communication, global system for mobile communications) receives increasing concern.
Intelligent antenna technology can utilize the spatial transmission characteristic of signal and interference different, carries out airspace filter, enhancing signal and inhibition interference etc.Intelligent antenna technology adopts many antenna sets of apart to become antenna array, and the received signal of each array element realizes directional reception through suitable weighted sum.Weighted sum essence is to adjust the amplitude and the phase place of each road signal, the desired signal coherent superposition is enhanced, and interference cancellation is inhibited.One group of beam pattern that weighing vector is corresponding certain.Adaptive beam in the smart antenna forms technology then can regulate weighing vector automatically according to the feature of received signal, make the main lobe of beam pattern aim at the desired signal direction, and wave beam zero sunken (or part zero falls into) is aimed at interference radiating way, thereby plays the effect that inhibition is disturbed.For up reception, the performance that adaptive beam forms skill has determined the improvement degree of antenna system to communication system.Since the nineties in 20th century, people form the application of technology in communication to adaptive beam and have carried out a large amount of theoretical researches.Yet because aspects such as implementation complexity and robustnesss, practical application is also less.
" a kind of real-time intelligent antenna processing device " (AReal-Time DOA-Based Smart Antenna Processor that Alexander Kuchar proposes based on DOA, IEEE Transaction on VehicularTechnology, Vol.51, pp.1279-1293, Nov.2002), the adaptive beam formation method of this real-time intelligent antenna processing device comprises as follows: carry out the orientation at first to received signal and estimate, judge that then all directions are desired signals or disturb, the weights that form according to the direction distribution design wave beam of desired signal and interference are weighted summation according to weights at last and form adaptive beam then.There is following defective in this technology: amount of calculation is big, realizes that complexity and robustness are poor.
Chinese invention patent CN1797985A discloses a kind of smart antenna self-adapting wave beam and has formed and data demodulation method, and this method comes down to the least square wave beam formation method that a kind of diagonal angle loads, and its diagonal loading amount is a noise power.This method loads by the diagonal angle and can avoid singular matrix is inverted, improve the robustness that adaptive beam forms, but this method needs the conditional number of estimation space covariance matrix, increased amount of calculation, and when utilizing noise power to carry out the diagonal angle loading, if high Signal to Interference plus Noise Ratio, its diagonal loading amount that adopts is less, and wave beam forms and has unsane problem.
In summary, existing adaptive beam forms technical scheme on reality is used, and obviously has inconvenience and defective, so be necessary to be improved.
Summary of the invention
At above-mentioned defective, first purpose of the present invention is to provide a kind of adaptive beam formation method, and this method can reduce amount of calculation in the process that forms adaptive beam, improve the robustness that wave beam forms, and realizes simple.
Second purpose of the present invention is to provide a kind of adaptive beam to form device, and this device can reduce amount of calculation in the process that forms adaptive beam, improve the robustness that wave beam forms, and realizes simple.
In order to realize above-mentioned first purpose, the invention provides the method that a kind of adaptive beam forms weights, described method comprises the steps:
A, after receiving the multi-channel sampling signal, obtain the signal to noise ratio of spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal;
B, obtain diagonal loading amount, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle and load according to described signal to noise ratio;
C, training sequence is modulated obtaining desired signal, and described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector;
D, generate adaptive beam and form weights, and form weights according to described adaptive beam described multi-channel sampling signal is weighted summation to export one road adaptive beam signal according to described spatial covariance matrix estimation and described associated vector after loading through the diagonal angle.
Adaptive beam forms the method for weights according to the present invention, among the described step B, obtains described diagonal loading amount according to described signal to noise ratio self adaptation; And/or
Described signal to noise ratio is the average signal-to-noise ratio of described multi-channel sampling signal.
Adaptive beam forms the method for weights, the linear or non-linear relation of described diagonal loading amount and average signal-to-noise ratio according to the present invention.
Adaptive beam forms the method for weights according to the present invention, and described diagonal loading amount L is according to formula:
Obtain, wherein, N is an array number, and SNR is an average signal-to-noise ratio.
Adaptive beam forms the method for weights according to the present invention, diagonal angle loading method among the described step B comprises: described diagonal loading amount and a unit diagonal matrix are multiplied each other obtains diagonal matrix, and with the matrix of described spatial covariance matrix estimation and described diagonal matrix with give described spatial covariance matrix estimation.
Adaptive beam forms the method for weights according to the present invention, among the described step D, generates described adaptive beam formation weights through spatial covariance matrix estimation after the diagonal angle loading and described associated vector according to minimum mean square error criterion according to described.
Adaptive beam forms the method for weights according to the present invention, and described adaptive beam forms weights
According to formula:
Calculate, wherein,
Be the spatial covariance matrix estimation after loading through the diagonal angle,
Be associated vector.
In order to realize above-mentioned second purpose, the invention provides a kind of adaptive beam and form device, comprise in the described device that adaptive beam forms module, described adaptive beam forms module and further comprises:
The spatial covariance matrix estimation submodule is used for obtaining spatial covariance matrix estimation according to described multi-channel sampling signal after receiving the multi-channel sampling signal;
The average signal-to-noise ratio calculating sub module of sampled signal is used for obtaining the signal to noise ratio of described multi-channel sampling signal according to described multi-channel sampling signal after receiving the multi-channel sampling signal;
The diagonal angle loads submodule, is used for obtaining diagonal loading amount according to described signal to noise ratio, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle loading;
Training sequence modulation submodule, be used for training sequence modulate with the symbol rotation to obtain desired signal;
The associated vector calculating sub module is used for described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector;
Adaptive beam forms submodule, is used for generating adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector;
The weighted sum submodule is used for forming weights according to described adaptive beam described multi-channel sampling signal is weighted summation to export one road adaptive beam signal.
Form device according to adaptive beam of the present invention, described diagonal angle loads submodule and is used for obtaining described diagonal loading amount according to described signal to noise ratio self adaptation, and/or be used for described diagonal loading amount and a unit diagonal matrix multiplied each other and obtain diagonal matrix, and with the matrix of described spatial covariance matrix estimation and described diagonal matrix with give described spatial covariance matrix estimation and the diagonal angle of described spatial covariance matrix estimation is loaded realizing.
Form device according to adaptive beam of the present invention, described adaptive beam forms submodule and is used for generating described adaptive beam formation weights through spatial covariance matrix estimation after the diagonal angle loading and described associated vector according to minimum mean square error criterion according to described.
Form device according to adaptive beam of the present invention, further comprise:
Signal pre-processing module is used for after this adaptive beam forms device and receives up multiple signals, carries out preliminary treatment obtaining baseband signal to this multi-channel sampling signal or to road sampled signal wherein, and this baseband signal sampled obtains sampled signal; And/or
The equalizing demodulation module is used for one road adaptive beam signal of described weighted sum submodule output is carried out equalizing demodulation.
The present invention obtains the average signal-to-noise ratio of spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal after receiving the multi-channel sampling signal; Obtain diagonal loading amount according to described average signal-to-noise ratio then, and described spatial covariance matrix estimation is carried out the diagonal angle loading according to described diagonal loading amount; Then training sequence is modulated obtaining desired signal, and described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector; Generate adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector at last, and described multi-channel sampling signal is weighted summation to export one road adaptive beam signal according to described adaptive beam formation weights.Whereby, the present invention has simplified beam forming process, has reduced amount of calculation, realizes simply, and has improved the robustness that wave beam forms greatly.
Description of drawings
Fig. 1 is that adaptive beam provided by the invention forms the apparatus module schematic diagram;
Fig. 2 is that the adaptive beam in the preferred embodiment of the present invention forms device handling principle figure;
Fig. 3 is that adaptive beam provided by the invention forms method flow diagram;
Fig. 4 is that the adaptive beam in the preferred embodiment of the present invention forms method flow diagram.
Embodiment
In order to make purpose of the present invention, technical scheme and advantage clearer,, the present invention is further elaborated below in conjunction with drawings and Examples.Should be appreciated that specific embodiment described herein only in order to explanation the present invention, and be not used in qualification the present invention.
Basic thought of the present invention is: utilize modulated training sequence as desired signal, and adopt self adaptation diagonal angle loading technique that spatial covariance matrix estimation is carried out the diagonal angle loading processing, generate adaptive beam formation weights then under based on MMSE (least mean-square error) principle, last weighted sum forms adaptive beam.
Adaptive beam provided by the invention forms device 100 as depicted in figs. 1 and 2, and described device 100 comprises: signal pre-processing module 101, adaptive beam form module 102 and equalizing demodulation module 103, wherein:
Signal pre-processing module 101 forms module 102 with adaptive beam and is connected, and is used for after adaptive beam forms device 100 to receive up multiple signals the x as Fig. 2
1(t), x
2(t), x
3(t) and x
4(t) four road signals carry out preliminary treatment such as filtering amplification, lower side frequency obtaining baseband signal to this multi-channel sampling signal or to road sampled signal wherein, and this baseband signal sampled obtain the x of sampled signal such as Fig. 2
1(k), x
2(k), x
3(k) and x
4(k) four tunnel sampled signals.This signal pre-processing module 101 and equalizing demodulation module 103 can be built in adaptive beam and form device 100, also can be placed on other communication equipments in the communication system.
Adaptive beam forms module 102, carrying out wave beam behind the multi-channel sampling signal that is used for received signal pretreatment module 101 is sent forms, concrete steps are: the signal to noise ratio that obtains spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal, obtain diagonal loading amount according to described signal to noise ratio then, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle and load, then training sequence is modulated to obtain desired signal, and described multi-channel sampling signal and described desired signal carried out related operation to obtain associated vector, generate adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector at last, and described multi-channel sampling signal is weighted summation to export one road adaptive beam signal according to described adaptive beam formation weights.
This adaptive beam forms module 102 and further comprises: the snr computation submodule 1022 of spatial covariance matrix estimation submodule 1021, sampled signal, diagonal angle load submodule 1023, training sequence modulation submodule 1024, associated vector calculating sub module 1025, adaptive beam formation submodule 1026 and weighted sum submodule 1027, wherein:
Spatial covariance matrix estimation submodule 1021 is used for obtaining spatial covariance matrix estimation according to described multi-channel sampling signal behind the multi-channel sampling signal that received signal pretreatment module 101 sends.
The snr computation submodule 1022 of sampled signal is used for obtaining the signal to noise ratio of described multi-channel sampling signal according to described multi-channel sampling signal behind the multi-channel sampling signal that received signal pretreatment module 101 sends.
Described signal to noise ratio can calculate according to training sequence and estimated channel, specifically can calculate referring to the baseband processing method that prior art provides, and does not expand herein.
The present invention, in order to reduce the influence of random perturbation, the snr computation submodule 1022 preferred signal to noise ratios to the multi-channel sampling signal of sampled signal average and obtain average signal-to-noise ratio SNR.
The diagonal angle loads submodule 1023, forming submodule 1026 with the snr computation submodule 1022 of spatial covariance matrix estimation submodule 1021, sampled signal with adaptive beam links to each other, be used for obtaining diagonal loading amount, and spatial covariance matrix estimation submodule 1021 resulting spatial covariance matrix estimation carried out the diagonal angle loading according to described diagonal loading amount according to snr computation submodule 1022 resulting signal to noise ratios (perhaps average signal-to-noise ratio) self adaptation of sampled signal.
Among the present invention, described self adaptation obtains diagonal loading amount and is meant when signal to noise ratio (perhaps average Signal to Interference plus Noise Ratio) is high, with the robustness of big diagonal loading amount with the formation of raising wave beam; When Signal to Interference plus Noise Ratio (perhaps average Signal to Interference plus Noise Ratio) hour, with the antijamming capability of little diagonal loading amount with the raising smart antenna.Linear or the non-linear relation of this diagonal loading amount and Signal to Interference plus Noise Ratio (perhaps average Signal to Interference plus Noise Ratio).Preferably, described diagonal loading amount L is according to formula:
Obtain, wherein, N is the array number of antenna array, and SNR is an average signal-to-noise ratio.
Training sequence modulation submodule 1024 is used for training sequence is modulated and the d (k) of symbol rotation to obtain desired signal such as Fig. 2.
Associated vector calculating sub module 1025, form submodule 1026 with adaptive beam and link to each other, be used for the described desired signal d (k) that described multi-channel sampling signal and training sequence modulation module 1027 obtain is carried out related operation to obtain the required associated vector of adaptive beam formation submodule 1026 with training sequence modulation submodule 1024.
The training sequence that training sequence modulation submodule 1024 of the present invention utilizes modulation has been simplified beam forming process as desired signal, has improved the robustness that wave beam forms.
Adaptive beam forms submodule 1026, load submodule 1023 with the diagonal angle and link to each other with associated vector calculating sub module 1025, the associated vector that spatial covariance matrix estimation after being used for loading according to the described diagonal angle that loads submodule 1023 through the diagonal angle and associated vector calculating sub module 1025 obtain generates the w of adaptive beam formation weights such as Fig. 2
1, w
2, w
3And w
4Deng weights.
The associated vector that spatial covariance matrix estimation after this adaptive beam formation submodule 1026 preferably loads according to described diagonal angle through diagonal angle loading submodule 1023 and described associated vector calculating sub module 1025 obtain generates described adaptive beam according to minimum mean square error criterion and forms weights.
Equalizing demodulation module 103 links to each other with weighted sum submodule 1027, is used for one road adaptive beam signal of weighted sum submodule 1027 outputs such as the y (k) of Fig. 2 are carried out equalizing demodulation.
Thus, form device 100 according to adaptive beam of the present invention and can regulate adaptive beam formation weights automatically, form main lobe, fall into and form zero at interference radiating way in sense.
Must state; the function that described adaptive beam formation device 100 can also load snr computation submodule 1022, the diagonal angle of spatial covariance matrix estimation submodule 1021, sampled signal submodule 1023, associated vector calculating sub module 1025 and adaptive beam formation submodule 1026 is integrated in the adaptive beam formation submodule 1026, and it is equally in protection scope of the present invention.
Fig. 3 is that adaptive beam provided by the invention forms method flow diagram, forms device 100 in conjunction with adaptive beam illustrated in figures 1 and 2 and is described, and this method comprises as follows:
Step S301, after receiving the multi-channel sampling signal, adaptive beam forms module 102 obtains spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal signal to noise ratio.
In this step, the spatial covariance matrix estimation submodule 1021 that is formed module 102 by adaptive beam is after receiving the multi-channel sampling signal, obtain spatial covariance matrix estimation according to described multi-channel sampling signal, obtain the signal to noise ratio (average signal-to-noise ratio) of described multi-channel sampling signal by the snr computation submodule 1022 of sampled signal according to described multi-channel sampling signal.
Step S302, adaptive beam forms module 102 and obtains diagonal loading amount according to described signal to noise ratio, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle loading.
In this step, the diagonal angle loads submodule 1023 and preferably obtains described diagonal loading amount according to described average signal-to-noise ratio self adaptation, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle loading.
Step S303, adaptive beam form module 102 training sequence are modulated obtaining desired signal, and described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector.
In this step, the training sequence modulation submodule 1024 that is formed module 102 by adaptive beam modulates training sequence to obtain desired signal, by associated vector calculating sub module 1025 described multi-channel sampling signal and described desired signal is carried out related operation to obtain associated vector.
Among the present invention, described step S303 can with step S301, step S302 exchanging order, do not influence the result that final wave beam forms.
Step S304, adaptive beam forms module 102 and generates adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector, and according to described adaptive beam formation weights described multi-channel sampling signal is weighted summation to export one road adaptive beam signal.
In this step, the adaptive beam that adaptive beam forms module 102 forms spatial covariance matrix estimation after submodule 1026 preferably loads according to the described diagonal angle that loads submodule 1023 through the diagonal angle and associated vector calculating sub module 1025 resulting associated vector and generates described adaptive beam according to minimum mean square error criterion and form weights, and weighted sum submodule 1027 forms adaptive beam that submodule 1026 generated according to adaptive beam and forms weights described multi-channel sampling signal is weighted summation to export one road adaptive beam signal then.
In order better to describe the present invention, the preferred embodiment of the present invention provide be applicable to gsm system the adaptive beam method of formationing as shown in Figure 4, be described in conjunction with adaptive beam formation device 100 illustrated in figures 1 and 2, this method specifically comprises as follows:
Step S401, adaptive beam form the multi-channel sampling signal that module 102 received signal pretreatment module 101 send.
In the present embodiment, described multi-channel sampling signal X is write as following matrix form:
Wherein, M is that array element number promptly exists M road sampled signal, and N is the sampling number of one tunnel sampled signal.
Step S402, spatial covariance matrix estimation submodule 1021 obtains spatial covariance matrix estimation according to described multi-channel sampling signal behind the multi-channel sampling signal that receives signal pre-processing module 101 transmissions.
Described spatial covariance matrix estimation
Obtain according to following formula:
Wherein, X is the multi-channel sampling signal, X
HBe multi-channel sampling signal, and N is the sampling number of one tunnel sampled signal through the symbol rotation.
Step S403, the snr computation submodule 1022 of sampled signal obtain the average signal-to-noise ratio SNR of described multi-channel sampling signal according to described multi-channel sampling signal.
Step S404, the diagonal angle loads submodule 1 023 and obtains diagonal loading amount L according to snr computation submodule 1022 resulting signal to noise ratios (perhaps average signal-to-noise ratio) self adaptation of sampled signal, and according to described diagonal loading amount to spatial covariance matrix estimation submodule 1021 resulting spatial covariance matrix estimation
Carrying out the diagonal angle loads.
In real system, because the influence of finite data length, and spatial covariance matrix estimation
Conditional number might be bigger, form if directly carry out wave beam according to the MMSE criterion, then robustness is relatively poor.Particularly, noiseless situation,
When unusual, it is then poorer that its wave beam forms robustness.In order to improve this situation, the diagonal angle loads 1023 pairs of spatial covariance matrix estimation of submodule to carry out the diagonal angle and loads, and be about to a described diagonal loading amount L and a diagonal matrix I of unit and multiply each other and obtain diagonal matrix LI, and with described spatial covariance matrix estimation
With the matrix of described diagonal matrix LI with give described spatial covariance matrix estimation
Promptly obtain through the spatial covariance matrix estimation after the diagonal angle loading
If diagonal loading amount L is too big, then antijamming capability can reduce, and if diagonal loading amount L is too little, then robustness is relatively poor.Therefore, diagonal angle of the present invention loads submodule 1023 according to current signal to noise ratio, the adaptive diagonal loading amount L that chooses.When Signal to Interference plus Noise Ratio is big, select to use bigger diagonal loading amount L, guaranteeing the robustness of weights, and Signal to Interference plus Noise Ratio hour selects to use less diagonal loading amount L, to guarantee the antijamming capability of weights.Diagonal loading amount and Signal to Interference plus Noise Ratio can be linear relationships, also non-linear relation.The diagonal angle loads submodule 1023 according to the adaptive acquisition diagonal loading amount of following formula L in the present embodiment:
Wherein, N is the sampling number of one tunnel sampled signal, and SNR is an average signal-to-noise ratio.
Step S405, training sequence modulation submodule modulate training sequence with symbol and rotate to obtain desired signal d.
In gsm system, among each NB (normal burst pulse train) training sequence is arranged, it is synchronous etc. to be used for channel estimating, burst sequence.The present invention, with this training sequence after the rotation of ovennodulation and symbol, as desired signal d.When reality realizes, this desired signal can be stored as constant, thereby reduce amount of calculation.
Step S406, associated vector calculating sub module 1025 is carried out related operation to obtain associated vector with described multi-channel sampling signal X and described desired signal d
Associated vector
Calculate according to following formula:
Wherein, X is the multi-channel sampling signal, d
HBe desired signal, and N is the sampling number of one tunnel sampled signal through the symbol rotation.
Step S407, adaptive beam form the spatial covariance matrix estimation after submodule 1026 loads according to described diagonal angle through diagonal angle loading submodule 1023
With associated vector calculating sub module 1025 resulting associated vector
Generate described adaptive beam according to the MMSE criterion and form weights
This adaptive beam forms weights
According to formula:
Calculate.
Step S408, weighted sum submodule 1027 forms the adaptive beam formation weights that submodule 1026 is generated according to adaptive beam
Described multi-channel sampling signal X is weighted summation to export one road adaptive beam signal.
In summary, the present invention obtains the average signal-to-noise ratio of spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal after receiving the multi-channel sampling signal; Obtain diagonal loading amount according to described average signal-to-noise ratio then, and described spatial covariance matrix estimation is carried out the diagonal angle loading according to described diagonal loading amount; Then training sequence is modulated obtaining desired signal, and described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector; Generate adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector at last, and described multi-channel sampling signal is weighted summation to export one road adaptive beam signal according to described adaptive beam formation weights.Whereby, the present invention has simplified beam forming process, has reduced amount of calculation, realizes simply, and has improved the robustness that wave beam forms greatly.
Certainly; the present invention also can have other various embodiments; under the situation that does not deviate from spirit of the present invention and essence thereof; those of ordinary skill in the art work as can make various corresponding changes and distortion according to the present invention, but these corresponding changes and distortion all should belong to the protection range of the appended claim of the present invention.
Claims (11)
1, a kind of adaptive beam formation method is characterized in that, described method comprises the steps:
A, after receiving the multi-channel sampling signal, obtain the signal to noise ratio of spatial covariance matrix estimation and described multi-channel sampling signal according to described multi-channel sampling signal;
B, obtain diagonal loading amount, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle and load according to described signal to noise ratio;
C, training sequence is modulated obtaining desired signal, and described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector;
D, generate adaptive beam and form weights, and form weights according to described adaptive beam described multi-channel sampling signal is weighted summation to export one road adaptive beam signal according to described spatial covariance matrix estimation and described associated vector after loading through the diagonal angle.
2, method according to claim 1 is characterized in that, among the described step B, obtains described diagonal loading amount according to described signal to noise ratio self adaptation; And/or
Described signal to noise ratio is the average signal-to-noise ratio of described multi-channel sampling signal.
3, method according to claim 2 is characterized in that, the linear or non-linear relation of described diagonal loading amount and average signal-to-noise ratio.
4, method according to claim 3 is characterized in that, described diagonal loading amount L is according to formula:
Obtain, wherein, N is an array number, and SNR is an average signal-to-noise ratio.
5, method according to claim 1, it is characterized in that, diagonal angle loading method among the described step B comprises: described diagonal loading amount and a unit diagonal matrix are multiplied each other obtains diagonal matrix, and with the matrix of described spatial covariance matrix estimation and described diagonal matrix with give described spatial covariance matrix estimation.
6, method according to claim 1 is characterized in that, among the described step D, generates described adaptive beam formation weights through spatial covariance matrix estimation after the diagonal angle loading and described associated vector according to minimum mean square error criterion according to described.
7, method according to claim 6 is characterized in that, described adaptive beam forms weights
According to formula:
Calculate, wherein,
Be the spatial covariance matrix estimation after loading through the diagonal angle,
Be associated vector.
8, a kind of adopt as claim 1～7 as described in each adaptive beam of method form device, it is characterized in that comprise in the described device that adaptive beam forms module, described adaptive beam forms module and further comprises:
The spatial covariance matrix estimation submodule is used for obtaining spatial covariance matrix estimation according to described multi-channel sampling signal after receiving the multi-channel sampling signal;
The average signal-to-noise ratio calculating sub module of sampled signal is used for obtaining the signal to noise ratio of described multi-channel sampling signal according to described multi-channel sampling signal after receiving the multi-channel sampling signal;
The diagonal angle loads submodule, is used for obtaining diagonal loading amount according to described signal to noise ratio, and according to described diagonal loading amount described spatial covariance matrix estimation is carried out the diagonal angle loading;
Training sequence modulation submodule, be used for training sequence modulate with the symbol rotation to obtain desired signal;
The associated vector calculating sub module is used for described multi-channel sampling signal and described desired signal are carried out related operation to obtain associated vector;
Adaptive beam forms submodule, is used for generating adaptive beam formation weights according to described through spatial covariance matrix estimation after the diagonal angle loading and described associated vector;
The weighted sum submodule is used for forming weights according to described adaptive beam described multi-channel sampling signal is weighted summation to export one road adaptive beam signal.
9, device according to claim 8, it is characterized in that, described diagonal angle loads submodule and is used for obtaining described diagonal loading amount according to described signal to noise ratio self adaptation, and/or be used for described diagonal loading amount and a unit diagonal matrix multiplied each other and obtain diagonal matrix, and with the matrix of described spatial covariance matrix estimation and described diagonal matrix with give described spatial covariance matrix estimation and the diagonal angle of described spatial covariance matrix estimation is loaded realizing.
10, device according to claim 8, it is characterized in that described adaptive beam forms submodule and is used for generating described adaptive beam formation weights through spatial covariance matrix estimation after the diagonal angle loading and described associated vector according to minimum mean square error criterion according to described.
11, device according to claim 8 is characterized in that, described device further comprises:
Signal pre-processing module is used for after this adaptive beam forms device and receives up multiple signals, carries out preliminary treatment obtaining baseband signal to this multi-channel sampling signal or to road sampled signal wherein, and this baseband signal sampled obtains sampled signal; And/or
The equalizing demodulation module is used for one road adaptive beam signal of described weighted sum submodule output is carried out equalizing demodulation.
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| US9325532B2 (en) * | 2003-06-30 | 2016-04-26 | Avago Technologies General Ip (Singapore) Pte. Ltd. | Method and apparatus for communicating symbols in a multiple input multiple output communication system using interleaved subcarriers across a plurality of antennas |
| CN100401650C (en) * | 2004-12-24 | 2008-07-09 | 中兴通讯股份有限公司 | Self-adaptive method of intelligent antenna for forming wave packet and demodulating data |
| CN100512052C (en) * | 2005-04-28 | 2009-07-08 | 上海原动力通信科技有限公司 | Beam shaping method for inhibiting interferes |
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